Modernizing the Brazilian active control network

The Brazilian Network for Continuous Monitoring of GPS - RBMC, since its foundation in December of 1996, has been playing an essential role for the maintenance and user access of the fundamental geodetic frame in the country,. It provides users with a direct link to the Brazilian Geodetic System - SGB. Its role has become more relevant with the increasing use of space navigation technology in the country. Recently, Brazil adopted a new geodetic system, SIRGAS2000, in February 2005, fully compatible with GNSS technology. The paper provides an overview of the recent modernization phases the RBMC network has undergone highlighting its future steps. From its current post-mission mode, the RBMC will evolve into a real-time network, providing real-time data and real-time correction to users. The network enhanced with modern GPS receivers and the addition of atomic clocks will be used to compute WADGPS-type corrections to be transmitted, in real time, to users in Brazil and surrounding areas. It is estimated that users will be able to achieve a horizontal accuracy around 0.5 m (1σ) in static and kinematic positioning and better for dual frequency users. The availability of the WADGPS service will allow users to tie to the new SIRGAS2000 system in a more rapid and transparent way for positioning and navigation applications. It should be emphasized that support to post-mission static positioning will continue to be provided to users interested in higher accuracy levels. In addition to this, a post-mission Precise Point Positioning (PPP) service will be provided based on the one currently provided by the Geodetic Survey Division of NRCan (CSRS-PPP). The modernization of the RBMC is under development based on a cooperation signed at the end of 2004 with the University of New Brunswick, supported by the Canadian International Development Agency and the Brazilian Cooperation Agency. The Geodetic Survey Division of NRCan is also participating in this modernization effort under the same project.

Antimony glasses with large nonlinear refractive indices, small two-photon absorption coefficients and ultrafast response at telecom wavelengths

Nonlinear (NL) optical properties of antimony oxide based glasses (AG) were characterized for excitation wavelengths from 800 to 1600 m. The NL refractive indices, n2, and the two-photon absorption (TPA) coefficient, β, have been evaluated using the Z-scan technique. Values of n2≈ 10-15 - 10-14 cm2/W of electronic origin were measured and negligible TPA coefficients (β < 0.003 cm/GW) were determined. The response time of the nonlinearity is faster than 100 fs as determined using the Kerr shutter technique. The figure-of-merit usually considered for all-optical switching, T = 2βλ/n2 , indicates that AG are very good materials for ultrafast switches at telecom wavelengths. © 2007 IEEE.

Comparative analysis of synchronization algorithms based on PLL, RDFT and Kalman Filter

This paper discusses the main characteristics and presents a comparative analysis of three synchronization algorithms based respectively, on a Phase-Locked Loop, a Kalman Filter and a Discrete Fourier Transform. It will be described the single and three-phase models of the first two methods and the single-phase model of the third one. Details on how to modify the filtering properties or dynamic response of each algorithm will be discussed in terms of their design parameters. In order to compare the different algorithms, these parameters will be set for maximum filter capability. Then, the dynamic response, during input amplitude and frequency deviations will be observed, as well as during the initialization procedure. So, advantages and disadvantages of all considered algorithms will be discussed. ©2007 IEEE.

Generating VRS data using atmospheric models: How far can we go?

Nowadays, with the expansion of the reference stations networks, several positioning techniques have been developed and/or improved. Among them, the VRS (Virtual Reference Station) concept has been very used. In this paper the goal is to generate VRS data in a modified technique. In the proposed methodology the DD (double difference) ambiguities are not computed. The network correction terms are obtained using only atmospheric (ionospheric and tropospheric) models. In order to carry out the experiments it was used data of five reference stations from the GPS Active Network of West of São Paulo State and an extra station. To evaluate the VRS data quality it was used three different strategies: PPP (Precise Point Positioning) and Relative Positioning in static and kinematic modes, and DGPS (Differential GPS). Furthermore, the VRS data were generated in the position of a real reference station. The results provided by the VRS data agree quite well with those of the real file data.

Variable structure control of switched systems based on Lyapunov-Metzler-SPR systems

This paper presents two Variable Structure Controllers (VSC) for continuous-time switched plants. It is assumed that the state vector is available for feedback. The proposed control system provides a switching rule and also the variable structure control input. The design is based on Lyapunov-Metzler (LM) inequalities and also on Strictly Positive Real (SPR) systems stability results. The definition of Lyapunov-Metzler-SPR (LMS) systems and its direct application in the design of VSC for switched systems are introduced in this paper. Two examples illustrate the design of the proposed VSC, considering a plant given by a switched system with a switched-state control law and two linear time-invariant systems, that are not controllable and also can not be stabilized with state feedback. ©2008 IEEE.

Foreign Direct Investment in Latin America and the Caribbean 2007

Includes bibliography

Weight vector estimation of circular arrays of antennas using Artificial Neural Networks

This paper presents a model for the control of the radiation pattern of a circular array of antennas, shaping it to address the radiation beam in the direction of the user, in order to reduce the transmitted power and to attenuate interference. The control of the array is based on Artificial Neural Networks (ANN) of the type RBF (Radial Basis Functions), trained from samples generated by the Wiener equation. The obtained results suggest that the objective was reached.

New contributions to the determination of resonance frequencies of rectangular microstrip antennas by neural networks

This paper uses artificial neural networks (ANN) to compute the resonance frequencies of rectangular microstrip antennas (MSA), used in mobile communications. Perceptron Multi-layers (PML) networks were used, with the Quasi-Newton method proposed by Broyden, Fletcher, Goldfarb and Shanno (BFGS). Due to the nature of the problem, two hundred and fifty networks were trained, and the resonance frequency for each test antenna was calculated by statistical methods. The estimate resonance frequencies for six test antennas were compared with others results obtained by deterministic and ANN based empirical models from the literature, and presented a better agreement with the experimental values.

Une architecture sensible au contexte pour le développement des systèmes d'administration pour l'enseignement

The increasing use of mobile devices and wireless communication technologies has improved the access to web information systems. However, the development of these systems imposes new challenges mainly due to the heterogeneity of mobile devices, the management of context information, and the complexity of adaptation process. Especially in this case, these systems should be runable on a great number of mobile devices models. In this article, we describe a context-aware architecture that provides solutions to the challenges presented above for the development of education administration systems. Copyright 2009 ACM.

Fault section estimation in automated distribution substations

In this paper, a methodology based on Unconstrained Binary Programming (UBP) model and Genetic Algorithms (GAs) is proposed for estimating fault sections in automated distribution substations. The UBP model, established by using the parsimonious set covering theory, looks for the match between the relays' protective alarms informed by the SCADA system and their expected states. The GA is developed to minimize the UBP model and estimate the fault sections in a swift and reliable manner. The proposed methodology is tested by utilizing a real-life automated distribution substation. Control parameters of the GA are tuned to achieve maximum computational efficiency and reduction of processing time. Results show the potential and efficiency of the methodology for estimating fault section in real-time at Distribution Control Centers. ©2009 IEEE.

Robust and fast vowel recognition using optimum-path forest

The applications of Automatic Vowel Recognition (AVR), which is a sub-part of fundamental importance in most of the speech processing systems, vary from automatic interpretation of spoken language to biometrics. State-of-the-art systems for AVR are based on traditional machine learning models such as Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs), however, such classifiers can not deal with efficiency and effectiveness at the same time, existing a gap to be explored when real-time processing is required. In this work, we present an algorithm for AVR based on the Optimum-Path Forest (OPF), which is an emergent pattern recognition technique recently introduced in literature. Adopting a supervised training procedure and using speech tags from two public datasets, we observed that OPF has outperformed ANNs, SVMs, plus other classifiers, in terms of training time and accuracy. ©2010 IEEE.

Competencia y regulación en las telecomunicaciones: el caso de Nicaragua

Incluye Bibliografía

Condiciones generales de competencia en Honduras

Incluye Bibliografía

Integrating open source codes for solid modeling and automatic mesh generation in FEM applications

The applications of the Finite Element Method (FEM) for three-dimensional domains are already well documented in the framework of Computational Electromagnetics. However, despite the power and reliability of this technique for solving partial differential equations, there are only a few examples of open source codes available and dedicated to the solid modeling and automatic constrained tetrahedralization, which are the most time consuming steps in a typical three-dimensional FEM simulation. Besides, these open source codes are usually developed separately by distinct software teams, and even under conflicting specifications. In this paper, we describe an experiment of open source code integration for solid modeling and automatic mesh generation. The integration strategy and techniques are discussed, and examples and performance results are given, specially for complicated and irregular volumes which are not simply connected. © 2011 IEEE.

Intrusion detection system using optimum-path forest

Intrusion detection systems that make use of artificial intelligence techniques in order to improve effectiveness have been actively pursued in the last decade. Neural networks and Support Vector Machines have been also extensively applied to this task. However, their complexity to learn new attacks has become very expensive, making them inviable for a real time retraining. In this research, we introduce a new pattern classifier named Optimum-Path Forest (OPF) to this task, which has demonstrated to be similar to the state-of-the-art pattern recognition techniques, but extremely more efficient for training patterns. Experiments on public datasets showed that OPF classifier may be a suitable tool to detect intrusions on computer networks, as well as allow the algorithm to learn new attacks faster than the other techniques. © 2011 IEEE.